STREAMING ANOMALY DETECTION

Computational methods and systems to detect anomalous behaving resources and objects of a distributed computing system are described. Multiple streams of metric data representing usage of various resources of the distributed computing system are sent to a management system of the distributed computing system. The management system updates a performance model based on newly received metric values of the streams of metric data. The updated performance model is used to detect changes in one or more of the streams of metric data. The changes may be an indication of anomalous behavior at resources and objects associated with the streams of metric data. An anomaly listener is notified of anomalous behavior by the resource or object when a change in one or more of the streams of metric data is detected.